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Analysis of Metric Spaces
Rating: 5.0 out of 5(2 ratings)
43 students

Analysis of Metric Spaces

The world according to Rudin
Created byDan Kucerovsky
Last updated 5/2023
English

What you'll learn

  • Effectively locate and use the information needed to prove theorems and establish mathematical results.
  • Effectively write mathematical solutions in a clear and concise manner.
  • Demonstrate an intuitive understanding of set theory and metric spaces
  • Understand the classic book Principles of Mathematical Analysis by Rudin

Course content

1 section24 lectures28h 32m total length
  • Introduction and Chapter 2 of Rudin1:23:13

    Explore infinity as a process and infinite sets (chapter two), define finite sets, and introduce set equivalence via bijections, setting the stage for topological and metric spaces.

  • Basic Set Theory57:53
  • Sequences1:07:56
  • Real and Rational Numbers1:04:58
  • The real numbers are uncountable1:09:21
  • Russel's paradox: not _everything_ can be a set1:58:06
  • More on Paradox... and the start of Metric Spaces1:08:32
  • Neighbourhoods in Metric space55:06
  • Interior Points, Open, Closed, and Clopen51:22
  • Dense Sets and Perfect sets52:20
  • Closed, bounded, compact56:05

    Analyze closed, bounded, and compact sets within metric spaces, clarifying how these properties interact and framing compactness in the context of metric space analysis.

  • Open is not the opposite of closed1:11:57
  • Not limits, but Limit Points. Closures.1:10:45
  • Compactness: a very clever generalization of closed intervals of the number line1:07:47
  • More on compactness59:27

    Examine compactness in metric spaces, showing compact sets are closed, and that in Euclidean space closed and bounded subsets are compact. Show continuous images of compact sets remain compact.

  • Review47:20
  • Properties of compact sets and of perfect sets1:00:24
  • The real line: Sequences and Series54:50
  • The Cantor set: Is it connected?58:04
  • Sequences in Metric Spaces49:31
  • More on sequences in Metric Spaces1:04:31
  • Another clever generalization: completeness through Cauchy sequences1:19:22
  • Comparing the two kinds of completeness4:00:00

    Explore the Cauchy criterion for convergence in sequences and metric spaces, and compare it with monotone completeness, series, and standard tests such as divergence and comparison.

  • Continuity: a property of maps of metric spaces43:55

Requirements

  • Mathematical maturity. In other words, be interested in mathematics.

Description

The methods of calculus are limited to Euclidean spaces. In this course, we show how the incredibly powerful tools of calculus, beginning with the limit concept, can be generalized to so-called metric spaces. Almost every space used in advanced analysis is in fact a metric space, and limits in metric spaces are a universal language for advanced analysis. The basic techniques of calculus were invented for the real line R. What should we do when we want to handle something more general than R? The fundamental notions of calculus begin with the idea that one point of R can be close to another point of R, and this is called "Approximation" or "taking a limit." Metrics are a way to transfer this key notion of being "close to" to a more general setting. The "points" of a metric space can be complicated objects in their own right. For example, they may themselves be functions on some other space. Ideas like this are ubiquitous in advanced mathematics today. One tries to throw away complicated details of the space being considered, and this makes it easier to see which theorem or technique can be applied next. In this way, the mathematician tries to avoid getting overwhelmed by the details, or to say it differently, we try to see the overall forest rather than the trees.

Who this course is for:

  • Have you tried to read the classic book Introduction to Mathematical Analysis by Rudin and been stimied? Take this course!